Information, Decision, & Complex Networks AFOSR/RTC Overview

Transcription

1 Information, Decision, & Complex Networks AFOSR/RTC Overview 06 MAR 2013 Integrity Service Excellence Robert J. Bonneau, Ph.D. Division Chief AFOSR/RTC Air Force Research Laboratory

2 Report Documentation Page Form Approved OMB No Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 06 MAR REPORT TYPE 3. DATES COVERED to TITLE AND SUBTITLE Information, Decision & Complex Networks AFOSR/RTC Overview 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Air Force Office of Scientific Research,AFOSR/RTC,875 N. Randolph,Arlington,VA, PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR S ACRONYM(S) 12. DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution unlimited 13. SUPPLEMENTARY NOTES Presented at the AFOSR Spring Review 2013, 4-8 March, Arlington, VA. 14. ABSTRACT 11. SPONSOR/MONITOR S REPORT NUMBER(S) 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT a. REPORT unclassified b. ABSTRACT unclassified c. THIS PAGE unclassified Same as Report (SAR) 18. NUMBER OF PAGES 7 19a. NAME OF RESPONSIBLE PERSON Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18

3 Information Decision and Complex Networks AFOSR/RTC Supported Key Air Force Technology Areas Include: Air and Space Situational Awareness/ISR, Autonomy, Cyber/C2 Technical Questions Addressed: How well modeled and structured is data in the problem? How inter-dependent, heterogeneous, and dynamic is the problem? Air/Space ISR Cyber/C2 Autonomy

4 AFOSR/RTC: Information Information: Problem has strong models such as from EM propagation and data characterized accordingly Example AF Problem: Sensor Resource Management Air and Space ISR Situational Awareness Sensing Resources Raw Sensor Data Waveform Sensing Degrees of Freedom Coordinated Action Mission Performance Verification Adaptive Resource Management Beamformer Aperture Sensing Requirements Not Met Sensing Requirements Met

5 AFOSR/RTC: Decision Decision: Problems have less well defined model requires human intervention/ analysis Example Problem: Human/Machine Behavior Modeling and Risk Characterization (Autonomy) Partially Autonomous Infrastructure Real Time Data Analytics Human Modeling & Sensing Autonomous Infrastructure Natural Language User Applications Physical Environ. Resource Const. Cultural Influence Social Media Social Network Machine Lower Mission Risk Online Mission Risk Analysis Human Lower Mission Risk

6 AFOSR/RTC: Complex Networks Complex Networks uses measured information to assure, manage, predict, and design distributed networks, systems, and architectures Heterogeneous Dynamic Air Force Systems Information Systems Research (System Measurement & Assessment) Complex Networks (Unified Mathematical Representation) Global System Global Network/Systems Research System Management Critical Information Local System System Measurement Network/Systems Management Research Preserve Critical Information Local Network/Systems Research Diverse Types of Systems System Properties

7 Information Decision and Complex Networks AFOSR/RTC Complex Networks/Foundations of Information Systems Robert Bonneau - mathematically represent networks of all kinds including communications and computational at all levels including content, protocol, and architecture/verify validate critical infrastructure performance Computational and Machine Intelligence/Mathematical Computational Cognition Jay Myung - objective is to maximize the ability of machines to conduct higher level cognitive activities with quantifiable risk and accurate models of human decision makers Dynamic Data Driven Application Systems Frederica Darema - enables analysis of the interplay between physical systems such as fluid dynamical systems and software systems and architectures as in the case of aircraft flight systems Information Operations and Security Robert Herklotz - looks at fundamental issues for assessing systems in terms of secure operations and mission assurance

8 Information Decision and Complex Networks AFOSR/RTC Science of Information Computation and Fusion Tristan Nguyen - enables the ability to collect, disseminate and integrate information in such a way as to mathematically characterize and assess the most appropriate information for a range of mission critical tasks Sensing Surveillance and Navigation Tristan Nguyen - develops algorithms to collect and decompose critical sensing information and enables techniques that interface between the physical domains such as electromagnetics and methods in navigation and geo-location Systems and Software Kathleen Kaplan - assesses these systems from a verification and validation standpoint to guarantee operations under a variety resource constraints Trust and Influence - Joe Lyons - seeks to model and measure the way collections of individuals make decisions and are influenced both in small groups and culturally